activity
20192023
most citedSignal Processing on PV Time-Series Data: Robust Degradation Analysis without Physical Models

34 citations · 40 across the 6 of their papers we have counts for

collaborators

6 papers

stat.AP2023

PV Fleet Modeling via Smooth Periodic Gaussian Copula

Mehmet G. Ogut, Bennet Meyers, Stephen P. Boyd

We present a method for jointly modeling power generation from a fleet of photovoltaic (PV) systems. We propose a white-box method that finds a function that invertibly maps vector…

eess.SP2022

Estimation of Soiling Losses in Unlabeled PV Data

Bennet Meyers

We provide a methodology for estimating the losses due to soiling for photovoltaic (PV) systems. We focus this work on estimating the losses from historical power production data t…

eess.SP2022

Estimation of Shade Losses in Unlabeled PV Data

Bennet Meyers, David Jose Florez Rodriguez

We provide a methodology for estimating the losses due to shade in power generation data sets produced by real-world photovoltaic (PV) systems. We focus this work on estimating sha…

cs.LG2022

Signal Decomposition Using Masked Proximal Operators

Bennet E. Meyers, Stephen P. Boyd

We consider the well-studied problem of decomposing a vector time series signal into components with different characteristics, such as smooth, periodic, nonnegative, or sparse. We…

eess.SY2019★ 6 cited

Statistical Clear Sky Fitting Algorithm

Bennet Meyers, Michaelangelo Tabone, Emre Can Kara

We present an algorithm that estimates a clear sky performance signal from the measured power of a PV system. The algorithm uses only observed power output, and assumes no knowledg…

eess.SP2019★ 34 cited

Signal Processing on PV Time-Series Data: Robust Degradation Analysis without Physical Models

Bennet Meyers, Michael Deceglie, Chris Deline +1

A novel unsupervised machine learning approach for analyzing time-series data is applied to the topic of photovoltaic (PV) system degradation rate estimation, sometimes referred to…